We are using a novel strategy to identify molecular targets for the therapy and prevention of common cancers, with an initial focus on colon cancer. The strategy capitalizes on data mining genomic information, generated and made available to the public through the NCI Cancer Genome Anatomy Project (CGAP), and combines this information with an experimental approach. Using tools provided by CGAP and developed in association with the LPG, we queried the CGAP database and found 665 sequences (genes, est's, and SAGE tags) expressed in colon cancer libraries and not in libraries from normal essential tissues. Of these, 356 are present on the Affymetrix HGU95 A-E chips, and thus became our experimental platform of choice. mRNA obtained from 16 normal essential tissues was assayed on the Affymetrix expression arrays and 242 of the sequences identified through data mining and present on the chips were found to be silent in all normal tissues assayed. We next assayed the RNA from colon cancer samples and identified 22 (22/242) sequences that were expressed in at least one of the colon cancer samples. Although the role of these 22 sequences is unknown at present, we anticipate that the initial investment spent delimiting targets not expressed in essential organs will facilitate the development of effective, non-toxic agents for cancer treatment. In addition to identifying targets of interest for drug development, it is clear that such targets could also be exploited for drug delivery, as early molecular markers of disease, or as surrogate markers for drug delivery and drug effectiveness. Thus, this general, systematic strategy should be useful in the identification of targets for the prevention and detection of many common cancers.